About
To date, knowledge on the interaction network between filovirus proteins and the host proteome (virhostome) are still extremely small and fragmented. These studies are limited to a few proteins such as VP24, VP35 and VP40. Although pathogenic EBOVs, Reston EBOV and MARVs are closely related and share identifiable genome organization, including similar open reading frames with high sequence similarities, these genera of viruses also exhibit significant differences in terms of pathogeny, but so far, no systematic or comparative approaches between different strains have been undertaken, making any correlation related to pathogenic traits extremely difficult and hazardous. The goal of this project is to identify human proteome targets of Ebolaviruses (EBOVs) and Marburgvirus (MARV) correlated to pathological traits. To address this issue virus-host interactomes (virhostomes) for highly pathogenic EBOVs (Zaire ebolavirus and current outbreak strains from Guinea, Sierra Leone, Nigeria and DRC) and Lake Victoria Marburg virus will be compared with apparently human-apathogenic EBOV species such as Reston ebolavirus. The project proposed herein is based on a new multiplexed high-throughput yeast two-hybrid system using a barcoded human ORFeome. Thanks to Next Generation Sequencing (NGS) this pipeline will allow to systematically map the network of binary interactions between viral proteins and the human proteome at a broad genomic scale. This screening includes for each viral species, NP, VP35, VP40, VP30, VP 24 and L proteins. Interaction hits are further validated with a high-throughput protein complementation assay based on a sensitive split-nanoluciferase system performed in vitro using human cell extracts. Our goal is to generate exhaustive and reliable interactomics datasets for filoviruses, including comparative studies between viral species and also characterize peptidic domains or mutations which are directly involved or susceptible to modify interaction properties. This strategy based on in-depth comparative analyses will allow to link specific interactomic properties with pathogenic traits providing a better understanding of pathophysiological mecanisms causing Ebola virus disease high lethality and will also identify potential targets for drug screening.